1. Field of the Invention
The present invention relates to an image processing apparatus including error diffusion processing by which green noise characteristics is added, an image processing method including error diffusion processing by which green noise characteristics is added and a computer readable storage medium storing a program thereof.
2. Description of Related Art
Conventionally, there is known a configuration where a green noise characteristic is added when binarizing an image by error diffusion processing (for example, see JP2008-219291 and Daniel L. Lau and Gonzalo R. Arce, “Modern Digital Halftoning”). Concentration of dots increases in the image to which green noise characteristic is added and the image is to have a frequency characteristic having number of frequency components of intermediate frequency.
FIG. 11 illustrates a basic conventional configuration of error diffusion processing by which a green noise characteristic is added.
An input unit 17 inputs a pixel value of multi-level notice pixel on a pixel to pixel basis. The first add unit 11 adds an error value diffused with respect to the notice pixel by the error diffusion unit 16 to the input value of the notice pixel which is input from the input unit 17 and outputs the sum thereof to the second add unit 12. The second add unit 12 adds the green noise value which is calculated by the green noise calculation unit 14 to the input value to which the error value is added and outputs the sum thereof to the threshold processing unit 13. The threshold processing unit 13 binarizes the input value to which the error value and the green noise value are added by using a threshold and output the binarized output value.
The green noise calculation unit 14 calculates the green noise value to be added to the notice pixel by using the output value which is output from the threshold processing unit 13. In particular, the green noise calculation unit 14 weights the output values of the pixels which are binarized by the threshold processing unit 13, the pixels positioning around the notice pixel, and obtains a green noise value by multiplying the sum of the weighted output values by a feedback coefficient. The calculated green noise value is added to the input value of the notice pixel by the second add unit 12.
The subtract unit 15 subtracts the input value of the notice pixel to which the error value is added by the first add unit 11 from the output value of the notice pixel which is output from the threshold processing unit 13 and calculates the error value before and after binarization. The error diffusion unit 16 weights the error value which is output from the subtract unit 15, and thereafter, diffuses the error value to the pixels which are not yet binarized by the threshold processing unit 13, which are positioning around the notice pixel. When the untreated surrounding pixels are to be treated as a notice pixel, the diffused error value is added to the input value of the surrounding pixels by the first add unit 11.
The above described error diffusion processing is a method for feeding back the output values of the binarized surrounding pixels to the pixel value of the notice pixel. When dots are to be output in the surrounding pixels of the notice pixel, a dot is also readily output in the notice pixel by the feedback. Therefore, dots tend to be concentrated. As a result, concentration of dots increases, and stable density reproduction and noise reduction can be realized.
However, according to the conventional configuration of adding green noise characteristics, when a halftone image area is treated after a halftone to high density image area and a low density image area are treated in this order, there may be a case where the original image cannot be sufficiently reproduced. For example, when thin lines are included in the halftone image area, the thin lines may be fragmentary.
This is because although dots are output intensively by the green noise value which is generated at the time of processing the halftone to high density image area, the image area to be treated next is in the low density area and generates a great negative error. The negative error is not canceled out when the low density image area is to be treated and is accumulated. The accumulated negative error acts greatly on untreated image so as not to output dots. That is, the negative error which is held in the low density image area is diffused in the halftone image area, and dots are not output where they should be output causing reproducibility of an original image be degraded in such way the halftone image area being partially missing.